Technical Content

The imaging of the complex fault system plays an important role in hydrocarbon exploration in Wenchang field since the fault system forms a bridge between the source rocks and reservoirs. However, it is challenging to obtain a high quality depth image of the fault ...

Much recent work has been done on comparing machine learning and geophysical inversion techniques to the extraction of model parameters from seismic reflection data. In our profession we are used to analyzing the physics of geophysical problems in detail. However, in many of the ...

The interpretation of fault surfaces is key to understanding the subsurface geology represented in 3D seismic volumes. The geologic structure represented by seismic reflections can be auto-tracked in the volume. Faults, however, are imaged as discontinuities or changes in curvature in the seismic data ...

Integrated exploration, new workflows for new challenges highlighting JumpStart Gabon, Marine Source Predictions and Encontrado reprocessing projects.

The paper presents a review of classic rock physics models used for clastic sedimentary rocks and how they have been combined into extended models through the introduction of a few parameters associated with a compositional or textural property of the rock. The models are ...

In recent years, there have been many rapid developments in subsurface imaging, meaning that even data sets that are only two or three years old can benefit from reprocessing. Reprocessing older data, either on its own or in combination with new data, is both ...

The world-class oil and gas fields of the Gippsland Basin, with original recoverable reserves of more than four billion barrels of oil and around ten trillion cubic feet of gas, were discovered following a 1962 2D seismic survey. Despite considerable exploration, it has long ...

Full-waveform inversion (FWI), proposed by Lailly and Tarantola in the 1980s, is considered the most promising data-driven tool to automatically build velocity models. Many successful examples have been reported using FWI to update shallow sediments, gas pockets, and mud volcanoes. However, successful applications of ...

Machine learning is rapidly becoming a standard technology within the oil and gas industry. This is especially true in petrophysics, where Big Data tend to need more efficient and faster data analysis. The term “machine learning” was coined in 1959 by Arthur Samuel and ...